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Abnormal (cancerous) blood cells, k-means, microscopic medical images, segmentation, classification
The aim of our work is to obtain a maximum rate of recognition of abnormal (cancerous) blood cells. We propose the development of a system based on k-means methods, after an RGB channel decomposition by applying the algorithm which can segment our microscopic medical images. It turns out that the proposed system shows better segmentation and classification for the identification and detection of leukemia. The experimental results obtained are very encouraging, which helps hematologists to monitor the evolution of cancerous blood cells and make a good diagnosis.
Abdellatif BOUZID-DAHO, Mohamed BOUGHAZI," Segmentation of Abnormal Blood Cells for Biomedical Diagnostic Aid", International Journal of Image, Graphics and Signal Processing(IJIGSP), Vol.10, No.1, pp. 30-35, 2018. DOI: 10.5815/ijigsp.2018.01.04
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